Automated Classification of chest X-ray images as normal or abnormal using Convolutional Neural Network
Chest X-Rays are generally used for diagnosing abnormalities in the thoracic area. Radiologists need to spend significant amount of time for interpreting scans. Automatic classification of these images could greatly help radiology interpretation process by enhancing real world diagnosis of problems. Hence, radiologists can focus on detecting abnormalities from the abnormal images rather than checking for it in all the images. In this paper, we present a machine learning approach to solve this problem. Here, the algorithm uses Convolutional Neural Networks (CNN) to learn and classify chest X-ray images as normal or abnormal based on image features.
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